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» Training Deformable Models for Localization
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CVPR
2005
IEEE
14 years 6 months ago
A Statistical Field Model for Pedestrian Detection
This paper presents a new statistical model for detecting and tracking deformable objects such as pedestrians, where large shape variations induced by local shape deformation can ...
Ying Wu, Ting Yu, Gang Hua
CVPR
2006
IEEE
14 years 6 months ago
Training Deformable Models for Localization
We present a new method for training deformable models. Assume that we have training images where part locations have been labeled. Typically, one fits a model by maximizing the l...
Deva Ramanan, Cristian Sminchisescu
ICCV
2011
IEEE
12 years 4 months ago
Scene Recognition and Weakly Supervised Object Localization with Deformable Part-Based Models
Weakly supervised discovery of common visual structure in highly variable, cluttered images is a key problem in recognition. We address this problem using deformable part-based mo...
Megha Pandey, Svetlana Lazebnik
PAMI
2011
12 years 11 months ago
Linear Local Models for Monocular Reconstruction of Deformable Surfaces
—Recovering the 3D shape of a nonrigid surface from a single viewpoint is known to be both ambiguous and challenging. Resolving the ambiguities typically requires prior knowledge...
Mathieu Salzmann, Pascal Fua
ISBI
2002
IEEE
14 years 5 months ago
Statistical shape model for automatic skull-stripping of brain images
This paper presents a statistical shape model for automatic skull stripping of MR brain images. A surface model of the brain boundary is hierarchically represented by a set of ove...
Zhiqiang Lao, Dinggang Shen, Christos Davatzikos